This study analyzes the spatial and temporal variability of PM₁₀ and PM_2.5 concentrations in Santo Domingo, Dominican Republic, based on short-term sampling campaigns conducted in 2019 and 2022. In 2019, PM₁₀ levels averaged 38.14 µg/m³, while in 2022 they rose significantly to 62.18 µg/m³. PM_2.5 in 2022 averaged 30.37 µg/m³. These differences are likely influenced by meteorological variability, including increased transport of Saharan dust in mid-2022, and seasonal factors. Although local emission changes were not directly assessed, they may have also played a role in the observed trends. Statistical analyses revealed that aerosol optical depth (AOD), air pressure, and rainfall were significant predictors of PM₁₀ in 2022, explaining up to 75% of the variance. Correlations and regression models confirmed a robust association between AOD and PM levels on a weekly timescale. These findings highlight the importance of integrating remote sensing and meteorological data to improve air quality monitoring and inform environmental policy in Caribbean urban areas.

This study assessed the concentrations and spatial patterns of heavy metals in fine particulate matter with aerodynamic diameter below 2.5 $\mu$m and coarse particulate matter with aerodynamic diameter below 10 $\mu$m in Santo Domingo, Dominican Republic, during 2022. Thirty 24 h samples were collected using portable low-volume samplers across representative urban environments. Elemental concentrations of arsenic, cadmium, chromium, copper, iron, manganese, nickel, lead, vanadium, and zinc were quantified by energy-dispersive X-ray fluorescence. To address data below detection limits, regression on order statistics was applied. Copper and zinc exhibited the highest mean concentrations, pointing to strong anthropogenic inputs, while vanadium and iron showed pronounced spatial variability. Principal component analysis identified traffic and industrial activities as dominant sources. These findings provide baseline evidence for heavy metal pollution in Caribbean urban air and emphasize the need for continuous monitoring and effective regulatory strategies to mitigate potential health risks.

The purpose of this article is to provide an analysis of the geochemistry of sediments deposited in the Bay of Samana (Dominican Republic) after 1900, emphasizing in the recent changes (last 20 years). This bay was formed by tectonism and sedimentation that joined the Samana peninsula with the northern mountain range. From 2003 to 2016, Dominican Republic was impacted by several cyclonic systems (storms and hurricanes), which caused an increase in the runoff of all rivers and streams that flow into the coastal area by depositing large amount of sediments in the basins of the rivers and tributaries. The Sedimentary Accumulation Rate (SAR) found in the cores indicates an increase in runoff which resulted in a decrease in the area and depth of the bay where sediment was deposited by rivers and streams. When analyzing data from the period 2003 to 2019, it was observed that the Yuna River has made an intrusion of sediment displacing 2.38 km(2) to the bay, its average SAR was 1.78 cm per year (cm y(-1)). The main cause of this increase in sediment deposition was mining, followed by deforestation, agriculture, and urban planning over the years, all activities that have the common denominator of being anthropic.

This study investigates the concentrations and spatial distribution of heavy metals in atmospheric particulate matter (PM2.5 and PM10) in Santo Domingo, Dominican Republic, during 2022. A total of 30 air samples were collected across diverse urban environments using portable low-volume samplers. Elemental analysis was performed via energy-dispersive X-ray fluorescence (EDXRF) to quantify levels of As, Cd, Cr, Cu, Fe, Hg, Mn, Ni, Pb, V, and Zn. Due to a high proportion of left-censored values, regression on order statistics (ROS) was employed to impute data below detection limits. The highest mean concentrations in both PM fractions were observed for Cu and Zn, indicating significant anthropogenic contributions, while V and Fe displayed marked spatial variability. Principal component analysis (PCA) suggested potential source groupings linked to traffic and industrial emissions. This work provides critical baseline data for urban air quality management in the region and highlights the need for expanded environmental monitoring to mitigate health risks associated with airborne heavy metals.